A memetic algorithm for the multi-compartment vehicle routing problem with stochastic demands

The multi-compartment vehicle routing problem (MC-VRP) consists of designing transportation routes to satisfy the demands of a set of customers for several products that, because of incompatibility constraints, must be loaded in independent vehicle compartments. Despite its wide practical applicability the MC-VRP has not received much attention in the literature, and the few existing methods assume perfect knowledge of the customer demands, regardless of their stochastic nature. This paper extends the MC-VRP by introducing uncertainty on what it is known as the MC-VRP with stochastic demands (MC-VRPSD). The MC-VRPSD is modeled as a stochastic program with recourse and solved by means of a memetic algorithm. The proposed memetic algorithm couples genetic operators and local search procedures proven to be effective on deterministic routing problems with a novel individual evaluation and reparation strategy that accounts for the stochastic nature of the problem. The algorithm was tested on instances of up to 484 customers, and its results were compared to those obtained by a savings-based heuristic and a memetic algorithm (MA/SCS) for the MC-VRP that uses a spare capacity strategy to handle demand fluctuations. In addition to effectively solve the MC-VRPSD, the proposed MA/SCS also improved 14 best known solutions in a 40-problem testbed for the MC-VRP.     

Symptoms prevalence among office employees and associations to building characteristics

A cross-sectional study was performed in eight companies, comprising 32 buildings without previously recognized indoor air problems. Engineers filled in a technical questionnaire on building characteristics, floor surface materials, ventilation, cleaning procedures, heating and cooling. A total of 3562 employees returned questionnaires on individual factors, workload, perceived physical work environment, allergy and symptoms. Frequent symptoms were feeling of fatigue or heavy-headedness, eye irritation, and dry facial skin. Women reported symptoms more frequently than men. Employees with allergy had a 1.8-2.5 times risk of reporting a high score for general, skin, or mucosal symptoms. The risk of a high symptom score increased with daily visual display unit (VDU) work time. Passive smoking and psychosocial load were also relatively strong predictors of symptoms. Weekly cleaning as compared with a frequency of cleaning two to four times a week increased the risk of symptoms. Adjusted odds ratio for a high general symptoms score from infrequent cleaning was 1.5 (95%CI 1.1-2.0). A high ventilation flow or central ventilation unit filter EU7 vs. EU8 seemed to be associated with an increased risk of general symptoms. Absence of local temperature control increased the risk of mucosal symptoms.     

HERSCHEL—PACS Bolometer Arrays for Submillimeter Ground-Based Telescopes

The Herschel Space Observatory will carry onboard a new kind of bolometric architecture for the PACS (Photodetector Array Camera and Spectrometer) submillimeter photometer. These new generation CCD-like multiplexed bolometer arrays are buttable and enable the conception of large fully sampled focal planes either for space or for ground-based telescopes. We present here some development for ground-based applications in the context of the ARTEMIS (ARchitecture de bolomètres pour des TElescopes sub-MIllimétriques au Sol) project. We have developed an electro-thermal numerical model that simulates the performances of these semiconducting bolometers under specific ground-based conditions (different wavelengths and background powers for example). This model permits to determine the optimal parameters for each condition and shows that the bolometers can be background limited in each atmospheric transmission window between 200 and 450 microns. We also describe the optical system that provides a high optical efficiency in each submillimeter atmospheric window. Astronomical observations made with a prototype on the APEX telescope are presented.     

Structure of Na Species in Promoted CaO-Based Sorbents and Their Effect on the Rate and Extent of the CO2 Uptake

To advance CaO-based CO₂ sorbents it is crucial to understand how their structural parameters control the cyclic CO₂ uptake. Here, CaO-based sorbents with varying ratios of Na₂CO₃:CaCO₃ are synthesized via mechanochemical activation of a mixture of Na₂CO₃ and CaCO₃ to investigate the effect of sodium species on the structure, morphology, carbonation rate and cyclic CO₂ uptake of the CO₂ sorbents. The addition of Na₂CO₃ in the range of 0.1–0.2 mol% improves the CO₂ uptake by up to 80% after 10 cycles when compared to ball-milled bare CaCO₃, while for Na₂CO₃ loadings >0.3 mol% the cyclic CO₂ uptake decreases by more than 40%. Energy dispersive X-ray spectroscopy (EDX), transmission electron microscopy, X-ray absorption spectroscopy (XAS), and ²³Na MAS NMR, reveal that in sorbents with Na₂CO₃ contents <0.3 mol% Na exists in highly distributed, noncrystalline [Na₂Ca(CO₃)₂] units. These species stabilize the surface area of the sorbent in pores of diameters >100 nm, and enhance the diffusion of CO₂ through CaCO₃. For Na₂CO₃ contents >0.3 mol%, the accelerated deactivation of the sorbents via sintering is related to the formation of crystalline Na₂Ca(CO₃)₂ and the high mobility of Na.     

High resolution electrical characterisation of organic photovoltaic blends

In this work, electrostatic force microscopy (EFM) and conductive atomic force microscopy (C-AFM) are applied to perform high-resolution electrical characterisation of organic photovoltaic films. These films are composed of the C₆₀-derivative PCBM blended with hole conductive conjugated polymers PPV derivatives or P3HT. It is demonstrated that both EFM and C-AFM are able to electrically evidence phase separation in the blends, suggesting in addition higher density of carriers along interfaces. Correlation between the EFM contrast and the photovoltaic properties of the blends was observed. Local spectroscopy (I-V curves) completes the C-AFM investigations, analysing charge transport mechanisms in the P3HT:PCBM blend. Significant modifications of the local electrical properties of P3HT are shown to occur upon blending. Space charge limited current is evidenced in the blend and a hole mobility of 1.7 × 10⁻² cm² V⁻¹ s⁻¹ is determined for P3HT.     

Combining Case-Based and Model-Based Reasoning for the Diagnosis of Complex Devices

A novel approach to integrating case-based reasoning with model-based diagnosis is presented. This approach, called Experience Aided Diagnosis (EAD), uses the model of the device and the results of diagnostic tests to index and match cases representing past diagnostic situations. Retrieved cases are then used to overcome errors created by the application of incorrect device models. The diagnostic methodology is described and applied to two real-world devices. Experimental results demonstrate the effectiveness of both the indexing schema and the matching algorithm. The paper discusses how these results can be generalized to multiple fault situations, to other types of device models, and to other applications in the field of an artificial intelligence.     

A Formal Model for Experience–Aided Diagnosis

This paper presents a novel approach to model–based diagnosis. The approach addresses the two main problems that have prevented model–based diagnostic techniques from being widely used: computational complexity of abduction and inadequacies of device models. A model for automated diagnosis is defined that combines (1) deduction to rule out hypotheses, (2) abduction to generate hypotheses, and (3) induction to recall past experiences and account for potential errors in the device models. A review of the three forms of inference is provided, as well as a detailed analysis of the relationship between case–based reasoning and induction. The proposed model for diagnosis is used to characterize diagnostic errors and relate them to different types of errors in the device models. Experimental results are then described and used to assert the practicality and the usefulness of the approach. The model presented in this paper yields a practical method for solving hard diagnostic problems at a reasonable computational cost and provides a theoretical basis for overcoming the problem of partially incorrect device models.